Construction of Early Warning Model for the New Psychoactive Substances Using in Adolescents

Based on the biological-psychology-sociological medicine pattern, this study aims to construction an early warning model of the New Psychoactive Substances (NPS) using for adolescents aged 14-35 years old. This study intends to obtain the data related to the behavioral expression of addiction susceptibility genes, adverse childhood experience, cognition, resistance and the use of NPS in adolescents by questionnaire survey (sample size: 200), and then use logistic regression and machine learning to construct an early warning model.

Based on the biological-psychology-sociological medicine pattern, this study aims to construction an early warning model on the use of the New Psychoactive Substances using for adolescents aged 14-35 years old. This study intends to conduct a questionnaire survey (sample size 200) to obtain data related to the behavioral expression of addiction susceptibility genes, childhood adversity experience, cognition, resistance and the use of NPS in adolescents from different regions and different populations. Through data analysis, this study aims to get the weight of different risk factors on NPS use, and then use logistic regression and machine learning to construct an early warning model, so as to screen out high-risk groups. At the same time, the expert group was consulted to establish a risk early warning system to provide a basis for intervention.